Bibliographic record
Abstract
This paper explores a culture and a research method, based on the conjecture that common similes and metaphors in a culture for “family” may offer insights into important aspects of the meanings, values, and ideals connected to family in that culture. With a focus on China, we looked for the first similes and metaphors for family that came up on the two most popular Chinese search engines, Baidu and Google. We winnowed the first hits, eliminating those that were not similes and metaphors and those that were to websites that few other websites linked to. In the end, we had nine Chinese similes and metaphors for family. They include: Family is a gentle harbor, a harbor for all seasons, a haven or refuge, a gas station, the center of the earth, and a little wooden boat on the river. We believe that these figures of speech represent Chinese cultural values that are important to Chinese thinking about families. Included in that, the figures of speech seem to us to represent the centrality of family in a society where for many the help they need will have to come from family. The method of investigating similes and metaphors for family as a way of understanding family in a culture has its risks, including issues of whose reality is reflected on websites and how search engines give priority to what comes up first in a search. But the method also seems worth considering as an addition to other social science tools for illuminating aspects of family life in a culture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".